[HTML][HTML] Large-scale evolutionary optimization: A review and comparative study
Large-scale global optimization (LSGO) problems have widely appeared in various real-
world applications. However, their inherent complexity, coupled with the curse of …
world applications. However, their inherent complexity, coupled with the curse of …
Learning to accelerate evolutionary search for large-scale multiobjective optimization
Most existing evolutionary search strategies are not so efficient when directly handling the
decision space of large-scale multiobjective optimization problems (LMOPs). To enhance …
decision space of large-scale multiobjective optimization problems (LMOPs). To enhance …
A survey on learnable evolutionary algorithms for scalable multiobjective optimization
Recent decades have witnessed great advancements in multiobjective evolutionary
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …
Neural net-enhanced competitive swarm optimizer for large-scale multiobjective optimization
The competitive swarm optimizer (CSO) classifies swarm particles into loser and winner
particles and then uses the winner particles to efficiently guide the search of the loser …
particles and then uses the winner particles to efficiently guide the search of the loser …
Competitive Swarm Optimizer: A decade survey
Since its inception in 2014, the Competitive Swarm Optimizer (CSO) has emerged as a
significant advancement in the field of swarm intelligence, particularly in addressing large …
significant advancement in the field of swarm intelligence, particularly in addressing large …
Robust multitask learning with sample gradient similarity
Multitask learning has led to great success in many deep learning applications during the
last decade. However, recent experiments have demonstrated that the performance of …
last decade. However, recent experiments have demonstrated that the performance of …
Cooperative particle swarm optimization with a bilevel resource allocation mechanism for large-scale dynamic optimization
Although cooperative coevolutionary algorithms are developed for large-scale dynamic
optimization via subspace decomposition, they still face difficulties in reacting to …
optimization via subspace decomposition, they still face difficulties in reacting to …
Surrogate-assisted evolutionary algorithm with decomposition-based local learning for high-dimensional multi-objective optimization
J Shen, P Wang, H Dong, W Wang, J Li - Expert Systems with Applications, 2024 - Elsevier
When the evolutionary algorithm is applied to handle high-dimensional expensive multi-
objective optimization problems (MOPs), population evolution is crucial since it controls …
objective optimization problems (MOPs), population evolution is crucial since it controls …
An adaptive two-stage evolutionary algorithm for large-scale continuous multi-objective optimization
This paper proposes an adaptive two-stage large-scale multi-objective evolutionary
algorithm, in which a neural network-based accelerating optimizer is designed in the first …
algorithm, in which a neural network-based accelerating optimizer is designed in the first …
Adaptive multi-objective competitive swarm optimization algorithm based on kinematic analysis for municipal solid waste incineration
W Huang, H Ding, J Qiao - Applied Soft Computing, 2023 - Elsevier
Multi-objective optimization for the municipal solid waste incineration process is considered
as a valuable technique to improve energy recovery and reduce pollutant emission …
as a valuable technique to improve energy recovery and reduce pollutant emission …